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View article: Denoising Diffusion Models on Model-Based Latent Space
Denoising Diffusion Models on Model-Based Latent Space Open
With the recent advancements in the field of diffusion generative models, it has been shown that defining the generative process in the latent space of a powerful pretrained autoencoder can offer substantial advantages. This approach, by a…
View article: Binary Classification of Agricultural Crops Using Sentinel Satellite Data and Machine Learning Techniques
Binary Classification of Agricultural Crops Using Sentinel Satellite Data and Machine Learning Techniques Open
The automated process of determining the crop type carried on plots of land, leveraging data provided by earth observation satellites, represents a highly valuable ability that can serve as a foundation for subsequent analyses or as input …
View article: Uncovering the Background-Induced bias in RGB based 6-DoF Object Pose Estimation
Uncovering the Background-Induced bias in RGB based 6-DoF Object Pose Estimation Open
In recent years, there has been a growing trend of using data-driven methods in industrial settings. These kinds of methods often process video images or parts, therefore the integrity of such images is crucial. Sometimes datasets, e.g. co…
View article: CERBERUS: Simple and Effective All-In-One Automotive Perception Model with Multi Task Learning
CERBERUS: Simple and Effective All-In-One Automotive Perception Model with Multi Task Learning Open
Perceiving the surrounding environment is essential for enabling autonomous or assisted driving functionalities. Common tasks in this domain include detecting road users, as well as determining lane boundaries and classifying driving condi…
View article: DCT-Former: Efficient Self-Attention with Discrete Cosine Transform
DCT-Former: Efficient Self-Attention with Discrete Cosine Transform Open
Since their introduction the Trasformer architectures emerged as the dominating architectures for both natural language processing and, more recently, computer vision applications. An intrinsic limitation of this family of "fully-attentive…
View article: All You Can Embed: Natural Language based Vehicle Retrieval with Spatio-Temporal Transformers
All You Can Embed: Natural Language based Vehicle Retrieval with Spatio-Temporal Transformers Open
Combining Natural Language with Vision represents a unique and interesting challenge in the domain of Artificial Intelligence. The AI City Challenge Track 5 for Natural Language-Based Vehicle Retrieval focuses on the problem of combining v…
View article: All You Can Embed: Natural Language based Vehicle Retrieval with\n Spatio-Temporal Transformers
All You Can Embed: Natural Language based Vehicle Retrieval with\n Spatio-Temporal Transformers Open
Combining Natural Language with Vision represents a unique and interesting\nchallenge in the domain of Artificial Intelligence. The AI City Challenge Track\n5 for Natural Language-Based Vehicle Retrieval focuses on the problem of\ncombinin…
View article: All You Can Embed: Natural Language based Vehicle Retrieval with Spatio-Temporal Transformers
All You Can Embed: Natural Language based Vehicle Retrieval with Spatio-Temporal Transformers Open
Combining Natural Language with Vision represents a unique and interesting challenge in the domain of Artificial Intelligence. The AI City Challenge Track 5 for Natural Language-Based Vehicle Retrieval focuses on the problem of combining v…